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Single-layer neural networks can be trained using various learning algorithms. The best-known algorithms are the Adaline, Perceptron and Backpropagation algorithms for supervised learning. The first two are specific to single-layer neural networks wh
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小波神经网络好文章！A method for fault detection is proposed using a trained neural network as the nominal
model of the system to be monitored. Partial physical knowledge, if available, can be combined
with the nominal model to perform fault isolation.
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neural network utility is a Neural Networks library for the
C++ Programmer. It is entirely object oriented and focuses
on reducing tedious and confusing problems of programming neural networks.
By this I mean that network layers are easily defi
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This function applies the Optimal Brain Surgeon (OBS) strategy for
％ pruning neural network models of dynamic systems. That is networks
％ trained by NNARX, NNOE, NNARMAX1, NNARMAX2, or their recursive
％ counterparts.-This function applies the
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Train a two layer neural network with a recursive prediction error
％ algorithm ("recursive Gauss-Newton"). Also pruned (i.e., not fully
％ connected) networks can be trained.
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％ The activation functions can either be linear or tanh. The netw
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matlab动量梯度下降算法
生成一个新的前向神经网络
对BP神经网络进行训练
对BP神经网络进行仿真-Momentum matlab gradient descent algorithm to generate a new feed-forward neural networks trained BP neural network on the BP neural network simulation
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Image Compression using Artificial Neural Networks
This code is developed in MATLAB 6.5 and can used in Windows platform. Program contain all necessary files. For training the network use Train.m and Codec.m compress images by trained network.
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The code implements a probabilstic Neuraol network for classification problems trained with a Leave One Out Cross Validation Scheme in Matlab (version 7 or above). The following toolboxes are required: statidtics, optimization and neural networks.
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In this paper, I present a novel hybrid face recognition approach based on a convolutional neural architecture, designed to robustly detect highly variable face patterns. With the weights of the trained neural networks there are created kernel window
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Abstract-This paper introduces the new concept of Artificial
Neural Networks (ANNs) in estimating speed and
controlling the separately excited DC motor. The neural
control scheme consists of two parts. One is the neural
estimator, which is us
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Multi-step-prediction of chaotic time series based
on co-evolutionary recurrent neural network
协同进化递归神经网络的多步混沌时间序列预测-This paper proposes a co-evolutionary recurrent neural network (CERNN) for the multi-step-prediction of chaotic
time series, it
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Neural networks are composed of simple elements operating in parallel. These
elements are inspired by biological nervous systems. As in nature, the network
function is determined largely by the connections between elements. We can
train a neura
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基于无迹卡尔曼滤波的人工神经网络matlab程序-Similar to using the extended Kalman filter, Neural Networks can also be trained through parameter estimation using the unscented Kalman filter.
This file provides a function for this purpose.
It also includes an exampl
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端至端卷积神经网络的文字识别,代码演示包.
它包含我们的论文中使用的所有主要组成部分: kmeans无监督特征学习 + 卷积神经网络(CNN)-This is a demo package of the code we used for our paper, "End-to-End
Text Recognition with Convolutional Neural Networks", T. Wang, D. Wu,
A. Coates, A. Ng, in ICPR 2012.
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基于bp神经网络和elman神经网络的图像压缩，mat文件是训练好的压缩结果，方便调用，可以测出信噪比等参数，用gui界面显示-Based on bp neural network and elman neural networks for image compression, mat file compression results are trained to facilitate the call, you can measure the signal to noise ratio and
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Describes the use of evolutionary algorithms to invert or explain trained neural networks.
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Golang实现的人工神经网络，可以进行训练和生成神经网络-Golang realization of artificial neural networks can be trained and generate neural network
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0A study on intrusion detection using neural networks trained with evolutionary algorithms
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可以打开视频文件或读取摄像头，通过训练好的RCNN进行金鱼的检测以及追踪。同时也可以自己训练需要检测追踪的物体。需要matlab2017以上版本。(You can open the video file or read the camera, through the trained Neural Networks of good RCNN goldfish detection and tracking. At the same time can also train their own need
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How to run the program
1. open MATLAB goto the project's root path
2. run main.m
3. in the command window it will show the accuracy calculated by testing data set
4. press any key in the command window to show the GUI for this project
5. click t
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